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Conducting psycholinguistic research online: Comparable evidence of second language lexical and sentence-level processing in web-based versus lab-based studies
Get PDFAlthough web-based data collection has become increasingly popular in (linguistic) research over the past years, many researchers are still cautious about collecting data via the internet. Thus, this study aims at comparing web-based and lab-based testing of linguistic manipulations that have resulted in robust findings in previous lab-based research on bilingual language processing. A total of 134 L1 German students of L2 English participated in two experiments in a web-based (n = 78) or lab-based setting (n = 56). The study examined potential language co-activation through cognates in an English Lexical Decision Task (Experiment 1) and the use of L2 lexical and syntactic information in English relative clause processing in a Self-paced Reading Task (Experiment 2). We found comparable evidence of lexical and syntactic processing in both groups in both experiments. Critically, this paper provides important methodological implications for web-based data collections with second language learners
Global consensus from the PHITT consortium surrounding an interim chemotherapy guidance for the treatment of children with hepatoblastoma, hepatocellular neoplasm – not otherwise specified (HCN-NOS), hepatocellular carcinoma and fibrolamellar carcinoma after trial closure
Get PDFMalignant liver tumors affecting children and adolescents are rare. In order to adequately study liver tumors occurring in this patient population and establish a more uniform approach to therapy, the three primary liver tumor consortia, SIOPEL (mainly European), COG (mainly North American) and JCCG (Japan), in concert, designed an international prospective clinical trial [PHITT (Paediatric Hepatic International Tumour Trial)/COGAHEP1531/JPLT4 – to be referred to as PHITT from this point forth] for the study of hepatoblastoma and hepatocellular carcinoma in children and adolescents. Recruitment to PHITT has recently concluded. The major results from this trial will be published in the next 2–3 years, therefore in the interim, we sought to provide a consensus statement on evidence-based chemotherapy guidance for hepatoblastoma and hepatocellular carcinoma of all stages
Wear, mechanical and chemical properties of castor oil toothbrush bristles
Get PDFManual toothbrushes with polyamide bristles are used for daily oral hygiene. Toothbrush bristles made from alternative raw materials like castor oil are increasingly produced but scarcely investigated. Medium hardness toothbrushes with bristles made of castor oil (AlterraBambus (ALT), Alverde (ALV), Dr. BestGreenClean (DRB), HydrophilBambus (HYD), ProkudentRecycling (PRO)) and one control toothbrush (ADAcontrol (ADA)) (n = 8) were investigated for wear, dentin-surface-roughness, elastic modulus and chemical composition. Toothbrushes were subjected to 12.5k, 25k, 37.5k and 50k cycles (toothbrush-simulator) simulating 6 months of toothbrushing. Macroscopic and microscopic (50 × magnification, SEM/micro-CT) images of bristle-ends, surface and overall quality were evaluated before and after mentioned intervals according to DIN_EN_ISO_20126. Data were statistically analyzed (Friedman-Test; ANOVA). No obvious wear was visible in macroscopic images. SEM-images showed acceptable bristle-ends in ADA (100 %) and DRB (100 %), PRO (96 %), ALV (87 %), ALT (82 %) and HYD (73 %), while bristle-surfaces were unacceptable only in HYD at 0 and 12.5k cycles. Overall evaluation was acceptable in ADA and DRB (100 %), PRO (96 %) ALV (84 %), ALT (82 %) and HYD (51 %) with significant difference in ALV and HYD at different intervals. Dentin-surface-roughness ranged from 3.4 to 3.8 μm (HYD-ALT), dentin-abrasion ranged from 60 to 95 μm (ALV-ALT) and elastic modulus ranged from 1.14 to 1.81 GPa (PRO-ALT) at baseline and from 0.61 to 1.11 GPa (PRO-ADA) after 50 k cycles. Bristles had similar elemental compositions: carbon (54.6–62.7 %), nitrogen (19.4–24.3 %) and oxygen (16.0–21.1 %), in agreement with ADA. Bristles of toothbrushes except HYD had acceptable bristle ends and surfaces. Dentin-surface-roughness, mechanical and chemical properties of castor oil bristles were similar to those of conventional polyamide bristles
Uncertainty quantification in ordinal classification: A comparison of measures
Get PDFUncertainty quantification has received increasing attention in machine learning in the recent past, but the focus has mostly been on standard (nominal) classification and regression so far. In this paper, we address the question of how to quantify uncertainty in ordinal classification, where class labels have a natural (linear) order. We reckon that commonly used uncertainty measures such as Shannon entropy, confidence, or margin are not appropriate for the ordinal case. In our search for better measures, we draw inspiration from the social sciences literature, which offers various measures to assess so-called consensus or agreement in ordinal data. We argue that these measures, or, more specifically, the dual measures of dispersion or polarization, do have properties that qualify them as measures of uncertainty. Furthermore, inspired by binary decomposition techniques for multi-class classification in machine learning, we propose a new method that allows for turning any uncertainty measure into an ordinal uncertainty measure in a generic way. We evaluate all measures in an empirical study on twenty-three ordinal benchmark datasets, as well as in a real-world case study on automotive goodwill claim assessment. Our studies confirm that dispersion measures and our binary decomposition method surpass conventional (nominal) uncertainty measures
Digital technology and language learning: insights from teachers of adult migrant learners
Get PDFIncreasing global digitalization is changing the everyday language skills required to participate in society, to carry out professional activities, and to take advantage of educational opportunities. As a result, new linguistic and digital competences are required for migrants. At the same time, digitalization offers new potential for learner-oriented language learning. In this article, we compare the results of two studies on teachers of adult multilingual migrant learners. These teachers instruct learners at different levels of literacy and with varied prior formal learning experiences. Both studies are situated in the German education system. The results illustrate how teachers and learners can work together using digital technologies to promote language learning. We explore the opportunities for effective, multilingual, and motivating language learning, as well as the challenges faced by learners and teachers, pointing to the need for further training in digital technology for both groups
A Multilingual Approach to Podcasting for Teaching and Learning Foreign Languages
Get PDFThe use of multilingual resources for foreign language learning has received increasing attention in recent years. This article presents a podcast project called Überall Konfetti – Il podcast italo‑tedesco che non ti aspetti, which incorporates both Italian and German in order to develop receptive language skills, while simultaneously providing socially relevant content. We then explore the reception of the podcast by means of a qualitative small group study conducted with students with different first languages. We finally provide a summary of the findings, discuss their pedagogical implications, and identify potential directions for further research
BTK‐Inhibition Enhances TLR‐7‐Mediated Interferon‐Alpha Production in pDCs by Blocking the Inhibitory BDCA‐2 Pathway
Get PDFIn pDCs, BTK-inhibition (BTKi) blocks the IFN-α production via TLR-9, but not via TLR-7. Upon TLR-7 stimulation, BTKi enhances the production of IFN-α by blocking the inhibitory BDCA-2 pathway. This might explain partially the failure of BTKi in SLE and is of interest for BTKi trials in multiple sclerosis
Neural correlates of false belief understanding in 33- to 36-month-old infants
Get PDFVery little research has addressed the neural correlates of false belief understanding in young children. Following up on a previous event-related potential (ERP) study examining false belief understanding in 4- to 6-year-old children, the present study grouped infants (N = 45, 33–36 months old) into passers and failers according to their behavioral performance on a low-demands false belief task. Their ERP responses to false belief and true belief conditions were examined in a novel ERP paradigm. The study found that a late positive waveform over the occipital electrode sites distinguished between the false belief and true belief conditions only in infants who passed the low-demands behavioral false belief task. In contrast, a late negative waveform over the frontocentral electrode sites consistently distinguished between the false belief and true belief conditions regardless of low-demands behavioral false belief task performance. These findings raise the possibility that a sensitive neural system supporting false belief understanding may emerge early in development. Specifically, the late positive waveform observed over the occipital electrode sites appears to be a potential neural marker for false belief understanding in infants
From rules to forests: rule-based versus statistical models for jobseeker profiling
No full textPublic employment services (PES) commonly apply profiling models to target labor market programs to jobseekers at risk of becoming long-term unemployed. Such allocation systems often codify institutional experiences in a set of profiling rules, whose predictive ability, however, is seldomly tested. We systematically compare the predictive performance of a rule-based profiling procedure currently used by the PES in Catalonia, Spain, with the performance of statistical models in predicting future long-term unemployment (LTU) spells. Using comprehensive administrative data, we develop logit and machine learning models and evaluate their performance with respect to both model discrimination and calibration. Compared to the rule-based model used in Catalonia, our machine learning models achieve greater discrimination ability and remarkable improvements in calibration. Particularly, our random forest model is able to accurately forecast LTU spells and outperforms the rule-based model by offering robust predictions that perform well under stress tests. This paper presents the first performance comparison between a complex, currently implemented, rule-based approach and complex statistical profiling models. Our work illustrates the importance of assessing the calibration of profiling models and the potential of statistical tools to assist public employment services
